Acutely or chronically ill persons may be immobilized during the course of their illness. This state of immobility leads to disuse of skeletal muscles, which in turn leads to immediate and progressive atrophy that results in profound muscle weakness over time. When the illness improves and the person is no longer immobile, the muscle weakness remains. Typically, a long rehabilitation period is required to recover function lost during a relatively short period of immobility. Prevention of immobility-based debilitation is challenging in the case of patients who are physically or mentally unable to participate in active exercise, for example critically-ill patients in the intensive care unit (ICU) of a hospital. These patients are often sedated or otherwise non-participative, eliminating voluntary exercise and the most beneficial forms of Physical Therapy from consideration. As a result, in most ICUs in the United States, literally nothing is done to prevent the onset of immobility-based debilitation and profound weakness.
Neuromuscular electrical stimulation (“NMES”) (also referred to as powered muscle stimulation, functional muscle stimulation, electrical muscle stimulation, and other terms) is a technology capable of activating a person's muscles involuntarily and non-invasively. However, despite recent studies that have both hypothesized and proven the benefit of NMES for use with bed-bound patients (e.g., see Zanotti et al, Chest 124:292-296, 2003 and Morris et al., Critical Care Clinics, 23:1-20, 2007, both incorporated herein by reference), it is not widely deployed in ICUs throughout the U.S. This is largely related to the labor-intensive nature of delivering effective NMES therapy. In clinical settings, labor-intensive protocols often inhibit the adoption of therapeutic treatments. This is particularly true in the ICU setting, where the primary care giver is an ICU nurse who spends his or her time split between patient care and other duties, such as charting. Most often, critical care nurses have their time fully committed, and cannot take on a new patient care activity without discarding another. Because debilitation-prevention is not vital to a critically ill person's immediate survival, NMES delivery would need to be very time-efficient in order for it to be implemented in the ICU setting. As virtually no ICU nurses are trained to deliver NMES, time-efficient delivery of this therapy by nursing staff in its current state-of-the-art form is not feasible. Given skyrocketing health-care costs, many institutions cannot afford or cannot justify hiring additional help, especially well-compensated advanced operators trained in delivering NMES.
One complicating factor that makes NMES difficult to deliver in a time-efficient manner is that each person responds differently to applied energy. Factors such as body-fat percentage, baseline muscle mass, and degree of skin hydration will all contribute to how well a person's muscles respond to a given energy intensity. Thus, it is often required to adjust stimulation parameters, such as pulse length, amplitude of applied voltage/current, and pulse-repetition frequency, on a case-by-case basis to ensure that a person receives effective therapy that is both safe and well-tolerated. Doing this task successfully is challenging. For example, it is well known that a stimulation energy intensity that simply produces visible muscle contraction is typically too low of an energy intensity for ideal therapeutic benefit. As illustrated by Snyder-Mackler and colleagues (Physical Therapy, Vol. 70, No. 10, 1994—incorporated herein by reference), stronger contractions often lead to better therapeutic outcomes than weaker contractions. Since it can be very difficult to visually differentiate varying degrees of moderate-to-strong muscle contraction (as opposed to binary assessments of contraction/no contraction) accurately, energy intensity adjustment is a tedious process and is often done sub-optimally. Even with a trained operator, parameter adjustment is typically an iterative and time-consuming process and still leads to sub-optimal results. This problem is exacerbated in the ICU, where untrained operators (nurses) would be required to make these assessments absent of any verbal feedback from non-communicative patients.
There are also safety issues related to the choice of stimulation parameters that may be operator-controlled. Current density, a function of injected charge, must be carefully controlled to avoid burns, nerve injury, and other potential complications (as detailed by Prausnitz Advanced Drug Delivery Reviews 18:395-425, 2006 and Stecker et al. Am J END Tech., 43:315-342, 2006, both of which are incorporated herein by reference). Thus, it is important not to grossly overestimate a person's energy intensity requirements in an attempt to maximize therapeutic benefit.
Further complications are related to the fact that ideal placement of stimulation electrodes may differ considerably from person-to-person. During stimulation of large muscle groups (ex. gluteals, quadriceps), electrode placement differences of less than 1 cm can reduce stimulation effectiveness by 50% or more. Precise electrode placement is required if muscles are to be activated effectively in a manner such that the person receiving therapy experiences minimal discomfort. Current methods to determine electrode placement involve initial estimations based upon anatomical markers, followed by iterative trial-and-error based adjustments based upon an observed muscle response. As with the required stimulation parameter adjustments noted above, finding suitable electrode locations proximal to muscle motor points is often labor-intensive endeavor.
The shortcomings of existing NMES technologies with regard to their ease-of use (particularly when used with challenging patients—such as the obese, elderly, and/or edematous) are widely recognized. To this end, several solutions have been proposed that include some type of sensor coupled to the stimulation pulse generator via feedback mechanisms. However, sensor-based solutions described in the prior art to date often function poorly, are costly and cumbersome to implement, and/or are inadequate for certain patient care scenarios. For example, EMG-based monitoring of muscle response during NMES is ineffective, because an EMG signal (amplitude on the order of mV) must be recorded in the same region and at the same time an NMES signal is delivered (amplitudes of up to ˜50V). This is especially true in scenarios where needle-based EMG electrodes are not used—i.e., situations where patient comfort, infection control, skin integrity management, or other concerns make their use inconvenient or unadvisable. Advanced signal processing algorithms or sophisticated filters may help improve signal-to-noise ratio, but in most situations these EMG signals are not adequate for successful optimization of NMES. As another illustrative example, accelerometer-based sensor systems have been proposed in the prior art as a way to self-optimize a muscle stimulator. However, accelerometers, strain gauges, and other displacement/strain/motion-based sensors fail in many clinical settings. For instance, in the ICU, sedated patients lie in bed with arms and legs fully or nearly-fully extended. Thus, contraction of important muscle groups such as the quadriceps and triceps produce little to no anatomical movement or acceleration, often resulting in unreliable accelerometer measurements of poor quality.
Existing NMES devices and technologies that are disclosed in the prior art do not include mechanisms to sufficiently improve ease of use and reduce therapy delivery time in high-demand clinical settings and with non-interactive patients. Further, previously-disclosed devices, systems, and methods of NMES do not teach robust sensor systems that are both robust enough and simple enough for use in these clinical environments. As a result, a proven-effective technology is not implemented in a large patient group that could benefit substantially from it.
A need still remains for devices, systems, and methods of use that can reduce implementation times for NMES by providing automated adjustment of stimulation parameters, energy delivery locations, or both. A secondary need also remains for devices, systems, and methods that improve the quality of NMES therapy by ensuring that optimal stimulation parameters and/or energy delivery locations are used on a per-person basis.